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Description
Grok Voice Think Fast 2.0 stands as the premier voice model from xAI, designed for the creation of real-time assistants, telephone agents, and interactive voice systems capable of bidirectional audio and text streaming via WebSocket. Developers have the flexibility to tailor various system parameters, such as the level of reasoning effort, the choice between built-in or custom voices, automatic voice activity detection on the server side, as well as configurable settings for silence duration, idle re-engagement, playback speed, and the ability to resume sessions following temporary disconnections. The model processes audio in several formats, including PCM, G.711 μ-law, G.711 A-law, and Opus, accepting both JSON and raw binary frames, with the adaptability to adjust PCM sample rates ranging from standard telephone quality to 48 kHz. It boasts support for over 20 languages with native-like accents, features automatic language recognition, generates natural responses in the user's preferred language, and facilitates smooth code-switching. Additionally, the inclusion of language hints and the ability to incorporate up to 100 key terms significantly enhance the accuracy of transcribing regional dialects, names, product identifiers, codes, addresses, and other specialized vocabulary, while pronunciation adjustments ensure the spoken output is correct and intelligible. This versatility makes Grok Voice Think Fast 2.0 an invaluable tool for developers looking to enhance user interaction through voice technology.
Description
Muse Voice Transcribe represents Meta’s inaugural venture into real-time audio perception, providing instantaneous automatic speech recognition (ASR), speaker diarization, and endpointing capabilities. This autoregressive multimodal model, part of the Muse Spark series, analyzes audio segments of 80 milliseconds and makes real-time decisions on whether to keep listening or to convert the spoken words into text. The adaptive delay mechanism allows it to adjust the audio context utilized for each word according to the complexity of the speech, thus optimizing the balance between transcription precision and response time. With training encompassing over 70 languages, 25 of which were rigorously validated at the time of its release, the model also seamlessly accommodates arbitrary code-switching, allowing transitions within and across sentences. Furthermore, language, keyword, and contextual biasing features enhance the recognition capabilities for specific names, locations, contacts, or specialized terms. The streaming diarization functionality enables the model to recognize shifts in speakers and can differentiate between more than 20 individual voices. Additionally, the endpointing feature is adept at identifying the commencement of speech and knowing when a user has completed their statement, ensuring a fluid interaction experience. Overall, Muse Voice Transcribe stands out as a cutting-edge tool in the realm of speech recognition technology, merging advanced features with user-friendly application.
API Access
Has API
API Access
Has API
Integrations
Grok
Grok Voice Agent
Grok Voice Agent Builder
Vercel AI Gateway
Integrations
Grok
Grok Voice Agent
Grok Voice Agent Builder
Vercel AI Gateway
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
SpaceXAI
Founded
2023
Country
United States
Website
docs.x.ai/developers/model-capabilities/audio/speech-to-speech
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
research.meta.ai/blog/introducing-muse-voice-transcribe